Abstract: In this paper, we analyze and test a scheme for the
estimation of electrical fundamental frequency signals from the
harmonic load current and voltage signals.
The scheme was based on using two different Multi Layer
Artificial Neural Networks (ML-ANN) one for the current and the
other for the voltage.
This study also analyzes and tests the effect of choosing the
optimum artificial neural networks- sizes which determine the quality
and accuracy of the estimation of electrical fundamental frequency
signals.
The simulink tool box of the Matlab program for the simulation of
the test system and the test of the neural networks has been used.
Abstract: In this paper we report a study aimed at determining
the effects of animation on usability and appeal of educational
software user interfaces. Specifically, the study compares 3
interfaces developed for the Mathsigner™ program: a static
interface, an interface with highlighting/sound feedback, and an
interface that incorporates five Disney animation principles. The
main objectives of the comparative study were to: (1) determine
which interface is the most effective for the target users of
Mathsigner™ (e.g., children ages 5-11), and (2) identify any Gender
and Age differences in using the three interfaces. To accomplish
these goals we have designed an experiment consisting of a
cognitive walkthrough and a survey with rating questions. Sixteen
children ages 7-11 participated in the study, ten males and six
females. Results showed no significant interface effect on user task
performance (e.g., task completion time and number of errors);
however, interface differences were seen in rating of appeal, with
the animated interface rated more 'likeable' than the other two.
Task performance and rating of appeal were not affected
significantly by Gender or Age of the subjects.
Abstract: The detection of outliers is very essential because of
their responsibility for producing huge interpretative problem in
linear as well as in nonlinear regression analysis. Much work has
been accomplished on the identification of outlier in linear
regression, but not in nonlinear regression. In this article we propose
several outlier detection techniques for nonlinear regression. The
main idea is to use the linear approximation of a nonlinear model and
consider the gradient as the design matrix. Subsequently, the
detection techniques are formulated. Six detection measures are
developed that combined with three estimation techniques such as the
Least-Squares, M and MM-estimators. The study shows that among
the six measures, only the studentized residual and Cook Distance
which combined with the MM estimator, consistently capable of
identifying the correct outliers.
Abstract: The occurrence of missing values in database is a serious problem for Data Mining tasks, responsible for degrading data quality and accuracy of analyses. In this context, the area has shown a lack of standardization for experiments to treat missing values, introducing difficulties to the evaluation process among different researches due to the absence in the use of common parameters. This paper proposes a testbed intended to facilitate the experiments implementation and provide unbiased parameters using available datasets and suited performance metrics in order to optimize the evaluation and comparison between the state of art missing values treatments.
Abstract: This paper aims to select the optimal location and
setting parameters of TCSC (Thyristor Controlled Series
Compensator) controller using Particle Swarm Optimization (PSO)
and Genetic Algorithm (GA) to mitigate small signal oscillations in a
multimachine power system. Though Power System Stabilizers
(PSSs) are prime choice in this issue, installation of FACTS device
has been suggested here in order to achieve appreciable damping of
system oscillations. However, performance of any FACTS devices
highly depends upon its parameters and suitable location in the
power network. In this paper PSO as well as GA based techniques are
used separately and compared their performances to investigate this
problem. The results of small signal stability analysis have been
represented employing eigenvalue as well as time domain response in
face of two common power system disturbances e.g., varying load
and transmission line outage. It has been revealed that the PSO based
TCSC controller is more effective than GA based controller even
during critical loading condition.
Abstract: Hearing impairment is the number one chronic
disability affecting many people in the world. Background noise is
particularly damaging to speech intelligibility for people with
hearing loss especially for sensorineural loss patients. Several
investigations on speech intelligibility have demonstrated
sensorineural loss patients need 5-15 dB higher SNR than the normal
hearing subjects. This paper describes Discrete Hartley Transform
Power Normalized Least Mean Square algorithm (DHT-LMS) to
improve the SNR and to reduce the convergence rate of the Least
Means Square (LMS) for sensorineural loss patients. The DHT
transforms n real numbers to n real numbers, and has the convenient
property of being its own inverse. It can be effectively used for noise
cancellation with less convergence time. The simulated result shows
the superior characteristics by improving the SNR at least 9 dB for
input SNR with zero dB and faster convergence rate (eigenvalue ratio
12) compare to time domain method and DFT-LMS.
Abstract: The heavy metal contamination of the technogenous
sediments and soils at the investigated dump-field show irregular
planar distribution. Also the heavy metal content in the surface water,
drainage water and in the groundwater was studied both in the dry as
well as during the rainy periods. The cementation process causes
substitution of iron by copper. Natural installation and development
of plant species was observed at the old mine waste dumps, specific
to the local chemical conditions such as low content of essential
nutrients and high content of heavy metals. The individual parts of
the plant tissues (roots, branches/stems, leaves/needles, flowers/
fruits) are contaminated by heavy metals and tissues are damaged
differently, respectively.
Abstract: In power systems, protective relays must filter their
inputs to remove undesirable quantities and retain signal quantities of
interest. This job must be performed accurate and fast. A new
method for filtering the undesirable components such as DC and
harmonic components associated with the fundamental system
signals. The method is s based on a dynamic filtering algorithm. The
filtering algorithm has many advantages over some other classical
methods. It can be used as dynamic on-line filter without the need of
parameters readjusting as in the case of classic filters. The proposed
filter is tested using different signals. Effects of number of samples
and sampling window size are discussed. Results obtained are
presented and discussed to show the algorithm capabilities.
Abstract: Missing data is a persistent problem in almost all
areas of empirical research. The missing data must be treated very
carefully, as data plays a fundamental role in every analysis.
Improper treatment can distort the analysis or generate biased results.
In this paper, we compare and contrast various imputation techniques
on missing data sets and make an empirical evaluation of these
methods so as to construct quality software models. Our empirical
study is based on NASA-s two public dataset. KC4 and KC1. The
actual data sets of 125 cases and 2107 cases respectively, without
any missing values were considered. The data set is used to create
Missing at Random (MAR) data Listwise Deletion(LD), Mean
Substitution(MS), Interpolation, Regression with an error term and
Expectation-Maximization (EM) approaches were used to compare
the effects of the various techniques.
Abstract: A method is presented for using thermo-mechanical fatigue analysis as a tool in the design of automotive heat exchangers. Use of infra-red thermography to measure the real thermal history in the heat exchanger reduces the time necessary for calculating design parameters and improves prediction accuracy. Thermal shocks are the primary cause of heat exchanger damage. Thermo-mechanical simulation is based on the mean behavior of the aluminum tubes used in the heat exchanger. An energetic fatigue criterion is used to detect critical zones.
Abstract: An active suspension system has been proposed to
improve the ride comfort. A quarter-car 2 degree-of-freedom (DOF)
system is designed and constructed on the basis of the concept of a
four-wheel independent suspension to simulate the actions of an
active vehicle suspension system. The purpose of a suspension
system is to support the vehicle body and increase ride comfort. The
aim of the work described in the paper was to illustrate the
application of fuzzy logic technique to the control of a continuously
damping automotive suspension system. The ride comfort is
improved by means of the reduction of the body acceleration caused
by the car body when road disturbances from smooth road and real
road roughness.
The paper describes also the model and controller used in the
study and discusses the vehicle response results obtained from a
range of road input simulations. In the conclusion, a comparison of
active suspension fuzzy control and Proportional Integration
derivative (PID) control is shown using MATLAB simulations.
Abstract: This paper presents an improvement method of
the multiple pitch estimation algorithm using comb filters.
Conventionally the pitch was estimated by using parallel
-connected comb filters method (PCF). However, PCF has
problems which often fail in the pitch estimation when there is
the fundamental frequency of higher tone near harmonics of
lower tone. Therefore the estimation is assigned to a wrong
note when shared frequencies happen. This issue often occurs
in estimating octave 3 or more. Proposed method, for solving
the problem, estimates the pitch with every harmonic instead of
every octave. As a result, our method reaches the accuracy of
more than 80%.
Abstract: The recent growth of using multimedia transmission
over wireless communication systems, have challenges to protect the
data from lost due to wireless channel effect. Images are corrupted
due to the noise and fading when transmitted over wireless channel,
in wireless channel the image is transmitted block by block, Due to
severe fading, entire image blocks can be damaged. The aim of this
paper comes out from need to enhance the digital images at the
wireless receiver side. Proposed Boundary Interpolation (BI)
Algorithm using wavelet, have been adapted here used to
reconstruction the lost block in the image at the receiver depend on
the correlation between the lost block and its neighbors. New
Proposed technique by using Boundary Interpolation (BI) Algorithm
using wavelet with Pixel interleaver has been implemented. Pixel
interleaver work on distribute the pixel to new pixel position of
original image before transmitting the image. The block lost through
wireless channel is only effects individual pixel. The lost pixels at the
receiver side can be recovered by using Boundary Interpolation (BI)
Algorithm using wavelet. The results showed that the New proposed
algorithm boundary interpolation (BI) using wavelet with pixel
interleaver is better in term of MSE and PSNR.
Abstract: To support user mobility for a wireless network new mechanisms are needed and are fundamental, such as paging, location updating, routing, and handover. Also an important key feature is mobile QoS offered by the WATM. Several ATM network protocols should be updated to implement mobility management and to maintain the already ATM QoS over wireless ATM networks. A survey of the various schemes and types of handover is provided. Handover procedure allows guarantee the terminal connection reestablishment when it moves between areas covered by different base stations. It is useful to satisfy user radio link transfer without interrupting a connection. However, failure to offer efficient solutions will result in handover important packet loss, severe delays and degradation of QoS offered to the applications. This paper reviews the requirements, characteristics and open issues of wireless ATM, particularly with regard to handover. It introduces key aspects of WATM and mobility extensions, which are added in the fixed ATM network. We propose a flexible approach for handover management that will minimize the QoS deterioration. Functional entities of this flexible approach are discussed in order to achieve minimum impact on the connection quality when a MT crosses the BS.
Abstract: This paper proposes an architectural and graphical
user interface (GUI) design of a traditional Thai musical instrument
application for tablet computers for practicing “Ranaad Ek" which is
a trough-resonated keyboard percussion instrument. The application
provides percussion methods for a player as real as a physical
instrument. The application consists of two playing modes. The first
mode is free playing, a player can freely multi touches on wooden bar
to produce instrument sounds. The second mode is practicing mode
that guilds the player to follow percussions and rhythms of practice
songs. The application has achieved requirements and specifications.
Abstract: In this paper a novel algorithm is proposed to merit
the accuracy of finger vein recognition. The performances of
Principal Component Analysis (PCA), Kernel Principal Component
Analysis (KPCA), and Kernel Entropy Component Analysis (KECA)
in this algorithm are validated and compared with each other in order
to determine which one is the most appropriate one in terms of finger
vein recognition.
Abstract: In this paper, the performance of two adaptive
observers applied to interconnected systems is studied. The
nonlinearity of systems can be written in a fractional form. The first
adaptive observer is an adaptive sliding mode observer for a Lipchitz
nonlinear system and the second one is an adaptive sliding mode
observer having a filtered error as a sliding surface. After comparing
their performances throughout the inverted pendulum mounted on a
car system, it was shown that the second one is more robust to
estimate the state.
Abstract: A new blind gray-level watermarking scheme is described. In the proposed method, the host image is first divided into 4*4 non-overlapping blocks. For each block, two first AC coefficients of its Hadamard transform are then estimated using DC coefficients of its neighbor blocks. A gray-level watermark is then added into estimated values. Since embedding watermark does not change the DC coefficients, watermark extracting could be done by estimating AC coefficients and comparing them with their actual values. Several experiments are made and results suggest the robustness of the proposed algorithm.
Abstract: A number of competing methodologies have been developed
to identify genes and classify DNA sequences into coding
and non-coding sequences. This classification process is fundamental
in gene finding and gene annotation tools and is one of the most
challenging tasks in bioinformatics and computational biology. An
information theory measure based on mutual information has shown
good accuracy in classifying DNA sequences into coding and noncoding.
In this paper we describe a species independent iterative
approach that distinguishes coding from non-coding sequences using
the mutual information measure (MIM). A set of sixty prokaryotes is
used to extract universal training data. To facilitate comparisons with
the published results of other researchers, a test set of 51 bacterial
and archaeal genomes was used to evaluate MIM. These results
demonstrate that MIM produces superior results while remaining
species independent.
Abstract: Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.